Group 1 - The global AI competition is shifting from a "sprint" of technological breakthroughs to a "marathon" of ecosystem building, with key variables being computing power costs, data quality, and scene implementation capabilities [1] - China aims to leverage its advantages in "green electricity + domestic chips," "data flow," and "scene sinking" to create a unique development path that combines technological breakthroughs with social benefits [1][2] - The high energy costs and chip supply limitations are major constraints on the global AI industry, and China's solution lies in integrating its renewable energy advantages with independent innovation to build a low-cost, high-security computing power supply system [1][2] Group 2 - The "Westward Migration" strategy of data centers is reshaping the cost structure of computing power, with regions like Qinghai and Inner Mongolia offering significantly lower electricity prices, thus reducing the costs of large model training [1] - The innovative "modular" chip cluster solution developed by Chinese companies allows for the combination of domestic 14nm chips to achieve performance equivalent to 3nm chips, drastically reducing training costs from tens of millions to millions [2] - The challenge of "data islands" and security concerns hinders the transformation of vast data into innovative momentum, but China's large-scale data base can provide continuous "live water" for AI development if data circulation barriers are broken [2][3] Group 3 - Innovations in data circulation are emerging across the country, with examples like Shenzhen's data element market and Hangzhou's "city brain" demonstrating the potential for increased efficiency when data is treated as a public resource [3] - The ultimate value of AI lies in solving real-world problems, and China's unique advantage is its comprehensive application scenarios from urban to rural areas, enabling AI to evolve from a "toy" to a "tool" [3][4] - Scene sinking is transforming traditional production methods, with AI applications in community markets and agriculture enhancing productivity and making technology accessible to ordinary people [4] Group 4 - The successful implementation of these three strategies relies on precise policy guidance, balancing innovation with resource management to prevent waste while allowing for experimentation [4]